Sampling-Based Hierarchical Trajectory Planning for Formation Flight

TL;DR

This paper introduces a hierarchical, sampling-based trajectory planning approach for UAV formation flight in cluttered environments, combining local sensing, formation guidance, and distributed optimization to enhance safety and formation maintenance.

Contribution

It presents a novel hierarchical trajectory planning framework integrating safe flight corridors, formation guidance, and distributed optimization for UAV formation flight.

Findings

Effective in dense obstacle environments

Ensures safe and smooth trajectories

Validated through comprehensive simulations

Abstract

Formation flight of unmanned aerial vehicles (UAVs) poses significant challenges in terms of safety and formation keeping, particularly in cluttered environments. However, existing methods often struggle to simultaneously satisfy these two critical requirements. To address this issue, this paper proposes a sampling-based trajectory planning method with a hierarchical structure for formation flight in dense obstacle environments. To ensure reliable local sensing information sharing among UAVs, each UAV generates a safe flight corridor (SFC), which is transmitted to the leader UAV. Subsequently, a sampling-based formation guidance path generation method is designed as the front-end strategy, steering the formation to fly in the desired shape safely with the formation connectivity provided by the SFCs. Furthermore, a model predictive path integral (MPPI) based distributed trajectory optimization method is developed as the back-end part, which ensures the smoothness, safety and dynamics feasibility of the executable trajectory. To validate the efficiency of the developed algorithm, comprehensive simulation comparisons are conducted. The supplementary simulation video can be seen at https://www.youtube.com/watch?v=xSxbUN0tn1M.